An adaptive equalizer based receiver, such as an NLMS-based receiver, provides superior performance for high data rate services such as frequency division duplex (FDD) high speed downlink packet access (HSDPA) or code division multiple access (CDMA) 2000 evolution data voice (EV-DV) over a Rake receiver. A typical NLMS receiver includes an equalizer having an equalizer filter and a tap coefficients generator. The equalizer filter is typically a finite impulse response (FIR) filter. The tap coefficients generator in the equalizer generates appropriate tap coefficients for the equalizer filter and uses an NLMS algorithm to update the tap coefficients appropriately and iteratively in a timely basis. The NLMS algorithm attempts to converge to a minimum mean square error (MMSE) solution by iteratively updating the tap coefficient weights such that, on average, they approach the MMSE solution.
Typically, an error signal computation, a vector norm calculation and leaky integration is required to generate and update the tap coefficients. When the optimal equalizer filter tap coefficients contain one or more zero values, it would be desirable to effectively remove some of the taps from the equalizer filter by masking the taps, rather than having the NLMS algorithm try to set the tap values to zero. The NLMS algorithm can only make the tap values small since there is always some noise perturbing the system and because step sizes cannot be made small in time varying channels. By masking the taps, the overall performance of the adaptive equalizer based receiver would be improved, especially when small delay spread channels or sparse channels are encountered.